What are the hardware requirements for Candle Mistral Trismegistus 7B?

Candle Mistral Trismegistus 7B requires approximately 14.4 GB of VRAM and supports a context window of 32K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Candle Mistral Trismegistus 7B and how large is it?

Candle Mistral Trismegistus 7B is developed by DanielClough, a model with 7b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Candle Mistral Trismegistus 7B perform on standard benchmarks?

Candle Mistral Trismegistus 7B has the following published scores: MMLU 54.49. Compare against reference models on this page or on the LLM Explorer leaderboards.

Candle Mistral Trismegistus 7B by DanielClough — VRAM 14.4GB, 32K context

Name: Candle Mistral Trismegistus 7B
Author: DanielClough

Candle Mistral Trismegistus 7B is an open-source language model by DanielClough. Features: 7b LLM, VRAM: 14.4GB, Context: 32K, License: apache-2.0, Quantized, LLM Explorer Score: 0.14, Arc: 54.1, HellaSwag: 77.9, MMLU: 54.5, GSM8K: 9.9.

Endpoints compatible Gguf Mistral Q4 Quantized Region:us Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/DanielClough/Candle_Mistral-Trismegistus-7B

Candle Mistral Trismegistus 7B Parameters and Internals

LLM Name	Candle Mistral Trismegistus 7B
Repository 🤗	https://huggingface.co/DanielClough/Candle_Mistral-Trismegistus-7B
Base Model(s)	Mistral Trismegistus 7B teknium/Mistral-Trismegistus-7B
Model Size	7b
Required VRAM	14.4 GB
Updated	2026-08-25
Maintainer	DanielClough
Model Type	mistral
Model Files	14.5 GB 2.4 GB 3.1 GB 4.1 GB 4.5 GB 4.1 GB 5.0 GB 5.4 GB 5.0 GB 5.9 GB 7.7 GB 8.2 GB 8.3 GB 9.9 GB: 1-of-2 4.5 GB: 2-of-2
GGUF Quantization	Yes
Quantization Type	q4\|gguf
Model Architecture	MistralForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.34.0.dev0
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32000
Torch Data Type	float16

Rank the Candle Mistral Trismegistus 7B capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation

Best Alternatives to Candle Mistral Trismegistus 7B

Best Alternatives	Context / RAM	Downloads	Likes
MegaBeam Mistral 7B 300K Gguf	282K / 5 GB	35	3
MegaBeam Mistral 7B 300K Gguf	282K / 5 GB	34	3
Backrooms Mistral 7B 10e	32K / 14.5 GB	128	0
Mistral 7B Instruct V0.2.gguf	32K / 14.5 GB	17	3
Mistral 7B Instruct V0.2 GGUF	32K / 4.4 GB	26	2
...andle Mistral 7B Instruct V0.2	32K / 14.4 GB	167	0
...andle Dolphin 2.2.1 Mistral 7B	32K / 14.4 GB	96	0
Boptruth Agatha 7B	32K / 14.4 GB	129	0
Mahou 1.2a Mistral 7B	32K / 14.4 GB	33	7
Tamil Mistral 7B Instruct V0.1	32K / 14.8 GB	350	14

Note: green Score (e.g. "73.2") means that the model is better than DanielClough/Candle_Mistral-Trismegistus-7B.